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Is it possible to create a new feature out of two, or more than two existing features using a decision tree? If so, how, and can it produce features with good information value that can better help the model?

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    $\begingroup$ Why would you use a decision tree? One tree usually is a weak predictor. What is the problem here: high dimensionality? $\endgroup$ – Peter May 3 at 9:35
  • $\begingroup$ No no, I'm trying to create a new feature, from the top features selected, based on an IV filter. I have seen people create categorical features using a decision tree, but I don't understand the idea. @Peter $\endgroup$ – Soumyajit Sarkar May 8 at 16:05

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